In industries such as banking, finance, and insurance, proper classification of data is critical to comply with a number of government regulations and to accurately characterize expected risks. The highly regulated yet dynamic nature of classification codes can make it challenging for professionals to stay current on exact numeric codes and associated definitions. This can result in a time consuming process of frequently researching, locating, and identifying proper classification codes using a number of industry sites and/or publications. As one example, when creating a new insurance policy for a business, an insurance professional can seek out and manually input the proper classification codes when entering various attributes that describe risks and/or operations of the business. There are typically multiple levels of classification that must be navigated through to accurately characterize the business customer. The risk of error or misclassification increases where multiple systems for classification code lookup are used and free-form manual data entry is performed.
When manual searches of various data sources are performed to determine classification codes, knowledge of contents and formatting of the data sources may be required. Data provided by different sources can use similar terms or ambiguous terms that may not be readily apparent without performing further searches to confirm that the code definitions are accurately understood. For example, the North American Industry Classification System (NAICS) provides a method for describing industries to which various organizations belong but includes many similar classifications such as: 445291 for Baked Goods Stores, 311811 for Retail Bakeries, 311812 for Commercial Bakeries, 311821 for Cookie and Cracker Manufacturing, 311919 for Other Snack Food Manufacturing, etc. Multiple coding schemes may be used for classifying businesses and types of operations performed by the businesses. If multiple individual searches of various databases occur across a computing network, then computer system and network performance is typically degraded, as each search requires processing resource time, network bandwidth, and temporary storage space to capture the results of multiple queries. Repeated data entry and numerous searches across multiple computer systems to retrieve similar and sometimes redundant information can reduce overall computer system and network performance.
In addition to searches for classifications that identify a business type, different job types for a specific business type may also need to be searched to accurately classify data when preparing an insurance policy. Job type code definitions can vary depending upon geographic location. Classification can be further complicated by the assignment of different classification codes for similar data depending upon geographic location. For example, in the insurance industry, workers compensation classification codes can be three or four digits as assigned by the National Council on Compensation Insurance (NCCI) or state rating bureaus. In the context of workers compensation insurance, over 700 unique classification codes exist, which serve as the basis for pricing and underwriting of workers compensation insurance policies. The classification codes help to differentiate between the various job duties or “scope of work performed” by employees.
Classification codes that are regulated by industry and geographic location are subject to change as time passes. Regulating bodies need not coordinate updates relative to each other, leading to any number of changes at any time throughout the year. The highly regulated yet dynamic nature of classification codes can make it challenging for professionals to stay current on exact numeric codes and associated definitions. This can result in a time consuming process of frequently researching, locating, and identifying proper classification codes using a number of industry sites and/or publications. As one example, when creating a new insurance policy, an insurance professional can seek out and manually input the proper classification codes when entering various attributes that describe risks and/or operations of the policy applicant. Multiple searches for both business type classification and job code classification can result in increased network and processing system bandwidth consumption and may further consume memory resources as multiple search results accumulate.